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      Gray and white matter changes associated with tool-use learning in macaque monkeys

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          Abstract

          We used noninvasive MRI and voxel-based morphometry (VBM) to detect changes in brain structure in three adult Japanese macaques trained to use a rake to retrieve food rewards. Monkeys, who were naive to any previous tool use, were scanned repeatedly in a 4-T scanner over 6 weeks, comprising 2 weeks of habituation followed by 2 weeks of intensive daily training and a 2-week posttraining period. VBM analysis revealed significant increases in gray matter with rake performance across the three monkeys. The effects were most significant (P < 0.05 corrected for multiple comparisons across the whole brain) in the right superior temporal sulcus, right second somatosensory area, and right intraparietal sulcus, with less significant effects (P < 0.001 uncorrected) in these same regions of the left hemisphere. Bilateral increases were also observed in the white matter of the cerebellar hemisphere in lobule 5. In two of the monkeys who exhibited rapid learning of the rake task, gray matter volume in peak voxels increased by up to 17% during the intensive training period; the earliest changes were seen after 1 week of intensive training, and they generally peaked when performance on the task plateaued. In the third monkey, who was slower to learn the task, peak voxels showed no systematic changes. Thus, VBM can detect significant brain changes in individual trained monkeys exposed to tool-use training for the first time. This approach could open up a means of investigating the underlying neurobiology of motor learning and other higher brain functions in individual animals.

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          Most cited references34

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          White matter in learning, cognition and psychiatric disorders.

          White matter is the brain region underlying the gray matter cortex, composed of neuronal fibers coated with electrical insulation called myelin. Previously of interest in demyelinating diseases such as multiple sclerosis, myelin is attracting new interest as an unexpected contributor to a wide range of psychiatric disorders, including depression and schizophrenia. This is stimulating research into myelin involvement in normal cognitive function, learning and IQ. Myelination continues for decades in the human brain; it is modifiable by experience, and it affects information processing by regulating the velocity and synchrony of impulse conduction between distant cortical regions. Cell-culture studies have identified molecular mechanisms regulating myelination by electrical activity, and myelin also limits the critical period for learning through inhibitory proteins that suppress axon sprouting and synaptogenesis.
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            Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE).

            A new three-dimensional imaging technique which is applicable for 3D MR imaging throughout the body is introduced. In our preliminary investigations we have acquired high-quality 3D image sets of the abdomen showing minimal respiratory artifacts in just over 7 min (voxel size 2.7 X 2.7 X 2.7 mm3), and 3D image sets of the head showing excellent gray/white contrast in less than 6 min (voxel size 1.0 X 2.0 X 1.4 mm3).
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              Cerebellar circuitry as a neuronal machine.

              Masao ITO (2006)
              Shortly after John Eccles completed his studies of synaptic inhibition in the spinal cord, for which he was awarded the 1963 Nobel Prize in physiology/medicine, he opened another chapter of neuroscience with his work on the cerebellum. From 1963 to 1967, Eccles and his colleagues in Canberra successfully dissected the complex neuronal circuitry in the cerebellar cortex. In the 1967 monograph, "The Cerebellum as a Neuronal Machine", he, in collaboration with Masao Ito and Janos Szentágothai, presented blue-print-like wiring diagrams of the cerebellar neuronal circuitry. These stimulated worldwide discussions and experimentation on the potential operational mechanisms of the circuitry and spurred theoreticians to develop relevant network models of the machinelike function of the cerebellum. In following decades, the neuronal machine concept of the cerebellum was strengthened by additional knowledge of the modular organization of its structure and memory mechanism, the latter in the form of synaptic plasticity, in particular, long-term depression. Moreover, several types of motor control were established as model systems representing learning mechanisms of the cerebellum. More recently, both the quantitative preciseness of cerebellar analyses and overall knowledge about the cerebellum have advanced considerably at the cellular and molecular levels of analysis. Cerebellar circuitry now includes Lugaro cells and unipolar brush cells as additional unique elements. Other new revelations include the operation of the complex glomerulus structure, intricate signal transduction for synaptic plasticity, silent synapses, irregularity of spike discharges, temporal fidelity of synaptic activation, rhythm generators, a Golgi cell clock circuit, and sensory or motor representation by mossy fibers and climbing fibers. Furthermore, it has become evident that the cerebellum has cognitive functions, and probably also emotion, as well as better-known motor and autonomic functions. Further cerebellar research is required for full understanding of the cerebellum as a broad learning machine for neural control of these functions.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                October 27 2009
                October 27 2009
                October 09 2009
                October 27 2009
                : 106
                : 43
                : 18379-18384
                Article
                10.1073/pnas.0909751106
                2759710
                19820167
                fc2dcdcb-1f21-4bd2-af7c-63fc58583ddc
                © 2009
                History

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